No behavioural evidence for rhythmic facilitation of perceptual discrimination

Lin, Wy Ming; Oetringer, Djamari; Bakker-Marshall, Iske; Emmerzaal, Jill; Wilsch, Anna; ElShafei, Hesham A.; Rassi, Elie; Haegens, Saskia

doi:10.1111/ejn.15208

Cited by 38 publications

(46 citation statements)

References 65 publications

(74 reference statements)

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“…These effects might be associated with entrainment, in which low-frequency neural oscillations in connection with fluctuations between periods of high and low neural sensitivity to the input and become phase-aligned to the external rhythmic stream such that periods of high sensitivity coincide with on-beat times of rhythmic stimuli ( Jones, 1976 ; Large and Jones, 1999 ; Barnes and Jones, 2000 ; Schroeder and Lakatos, 2009 ; Breska and Deouell, 2016 ). A handful of studies failed to find the rhythmic behavioral benefits ( Benwell et al, 2017 ; Ruzzoli et al, 2019 ; Vigué-Guix et al, 2020 ; Lin et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Effect of Tempo on Temporal Expectation Driven by Rhythms in Dual-Task Performance

Ren

Misaki

et al. 2021

Front. Psychol.

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Temporal expectation is the ability to focus attention at a particular moment in time to optimize performance, which has been shown to be driven by regular rhythms. However, whether the rhythm-based temporal expectations rely upon automatic processing or require the involvement of controlled processing has not been clearly established. Furthermore, whether the mechanism is affected by tempo remains unknown. To investigate this research question, the present study used a dual-task procedure. In a single task, the participants were instructed to respond to a visual target preceded by a regular or an irregular visual rhythm under a fast (500 ms) or slow (3,500 ms) tempo. The dual-task simultaneously combined a working memory (WM) task. The results showed temporal expectation effects in which the participants responded faster to the regular than to the irregular conditions in a single task. Moreover, this effect persisted under dual-task interference in the fast tempo condition but was impaired in the slow tempo condition. These results revealed that rhythmic temporal expectation induced by fast tempo was dependent on automatic processing. However, compared with the faster tempo, temporal expectation driven by a slower tempo might involve more controlled processing.

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Section: Introductionmentioning

confidence: 99%

Effect of Tempo on Temporal Expectation Driven by Rhythms in Dual-Task Performance

Ren

Misaki

et al. 2021

Front. Psychol.

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“…However, the evidence for persistent entrainment is sparse. Some behavioral studies have shown persistent effects of rhythmic input on subsequent responses (Hickok, Farahbod, & Saberi, 2015;Jones et al, 2002), though this has sometimes proven hard to replicate (Bauer, Jaeger, Thorne, Bendixen, & Debener, 2015;Lin et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A silent disco: Differential effects of beat-based and pattern-based temporal expectations on persistent entrainment of low-frequency neural oscillations

Bouwer¹,

Fahrenfort²,

Millard³

et al. 2020

Preprint

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Psychology, Vrije Universiteit Amsterdam (h.a.slagter@vu.nl). AbstractTemporal expectations (e.g., predicting "when") facilitate sensory processing, and are suggested to rely on entrainment of low frequency neural oscillations to regular rhythmic input.However, temporal expectations can be formed not only in response to a regular beat, such as in music ("beat-based" expectations), but also based on a predictable pattern of temporal intervals of different durations ("memory-based" expectations). Here, we examined the neural mechanisms underlying beat-based and memory-based expectations, by assessing EEG activity and behavioral responses during silent periods following rhythmic auditory sequences that allowed for beat-based or memory-based expectations, or had random timing. In Experiment 1 (N = 32), participants rated how well probe tones at various time points fitted the previous rhythm. Beat-based expectations affected fitness ratings for at least two beat-cycles, while the effects of memory-based expectations subsided after the first expected time point in the silence window. In Experiment 2 (N = 27), using EEG, we found a CNV following the final tones of memory-based and random, but not beat-based sequences, suggesting that climbing neuronal activity may specifically reflect memory-based expectations. Moreover, we found enhanced power in the EEG signal at the beat frequency for beat-based sequences both during listening and the silence. For memory-based sequences, we found enhanced power at a frequency inherent to the memory-based pattern only during listening, but not during the silence, suggesting that ongoing entrainment of low frequency oscillations may be specific to beatbased expectations. Finally, using multivariate pattern decoding on the raw EEG data, we could classify above chance from the silence which type of sequence participants had heard before.Together, our results suggest that beat-based and memory-based expectations rely on entrainment and climbing neuronal activity, respectively.

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“…The number of studies investigating rhythms in behavior has been growing in recent years (VanRullen, 2016a). However, different methods have been used to analyses these data, making the comparison between studies difficult, and concerns over reproducibility have been raised (Lin et al, 2021; Sun et al, 2021; van der Werf et al, 2021). Moreover, it is not clear which of these methods is more optimal to maximize the detection of true rhythms while minimizing the chance of false discoveries.…”

Section: Discussionmentioning

confidence: 99%

Quantifying rhythmicity in perceptual reports

Tosato

Rohenkohl

Dowdall

2022

Preprint

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Several recent studies investigated the rhythmic nature of cognitive processes that lead to perception and behavioral report. These studies used different methods, and there has not yet been an agreement on a general standard. Here, we present a way to test and quantitatively compare these methods. We simulated behavioral data from a typical experiment and analyzed these data with several methods. We applied the main methods found in the literature, namely sine-wave fitting, the Discrete Fourier Transform (DFT) and the Least Square Spectrum (LSS). DFT and LSS can be applied both on the averaged accuracy time course and on single trials. LSS is mathematically equivalent to DFT in the case of regular, but not irregular sampling - which is more common. LSS additionally offers the possibility to take into account a weighting factor which affects the strength of the rhythm, such as arousal. Statistical inferences were done either on the investigated sample (fixed-effect) or on the population (random-effect) of simulated participants. Multiple comparisons across frequencies were corrected using False-Discovery-Rate, Bonferroni, or the Max-Based approach. To perform a quantitative comparison, we calculated Sensitivity, Specificity and D-prime of the investigated analysis methods and statistical approaches. Within the investigated parameter range, single-trial methods had higher sensitivity and D-prime than the methods based on the averaged-accuracy-time-course. This effect was further increased for a simulated rhythm of higher frequency. If an additional (observable) factor influenced detection performance, adding this factor as weight in the LSS further improved Sensitivity and D-prime. For multiple comparison correction, the Max-Based approach provided the highest Specificity and D-prime, closely followed by the Bonferroni approach. Given a fixed total amount of trials, the random-effect approach had higher D-prime when trials were distributed over a larger number of participants, even though this gave less trials per participant. Finally, we present the idea of using a dampened sinusoidal oscillator instead of a simple sinusoidal function, to further improve the fit to behavioral rhythmicity observed after a reset event.

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No behavioural evidence for rhythmic facilitation of perceptual discrimination

Cited by 38 publications

References 65 publications

Effect of Tempo on Temporal Expectation Driven by Rhythms in Dual-Task Performance

Effect of Tempo on Temporal Expectation Driven by Rhythms in Dual-Task Performance

A silent disco: Differential effects of beat-based and pattern-based temporal expectations on persistent entrainment of low-frequency neural oscillations

Quantifying rhythmicity in perceptual reports

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